Update app.py

app.py

@@ -45,20 +45,20 @@ def predict(inp):
     encoders = [EncodecModel.from_pretrained("facebook/encodec_48khz")]
 
     #Run modelD to disguise audio
-    waveform = attack.poison_audio(waveform, sample_rate, encoders)
+    waveform, waveform2, waveform3, waveform4 = attack.poison_audio(waveform, sample_rate, encoders)
 
     #Transform output audio into gradio-readable format
     waveform = waveform.numpy()
     waveform = float32_to_int16(waveform)
-    '''waveformD = waveformD.numpy()
-    waveformD = float32_to_int16(waveformD)
-    waveformM = waveformM.numpy()
-    waveformM = float32_to_int16(waveformM)
-    waveformDM = waveformDM.numpy()
-    waveformDM = float32_to_int16(waveformDM)'''
+    waveform2 = waveform2.numpy()
+    waveform2 = float32_to_int16(waveform2)
+    waveform3 = waveform3.numpy()
+    waveform3 = float32_to_int16(waveform3)
+    waveform4 = waveform4.numpy()
+    waveform4 = float32_to_int16(waveform4)
 
     #return (sample_rate, waveformD), (sample_rate, waveformM), (sample_rate, waveformDM)
-    return (sample_rate, waveform), (sample_rate, waveform), (sample_rate, waveform)
+    return (sample_rate, waveform), (sample_rate, waveform2), (sample_rate, waveform3), (sample_rate, waveform4)
 
 #Set up gradio interface
 import gradio as gr